Scale-Space Theory in Computer Vision

A basic problem when deriving information from measured data,
such as images, originates from the fact that objects in the
world, and hence image structures, exist as meaningful entities
only over certain ranges of scale.
"Scale-Space Theory in Computer Vision" describes a
formal theory for representing the notion of scale in image data,
and shows how this theory applies to essential problems in computer
vision such as computation of image features and cues to surface shape.
The subjects range from the mathematical foundation to
practical computational techniques.
The power of the methodology is
illustrated by a rich set of examples.

This book is the first monograph on scale-space theory. It is intended
as an introduction, reference, and inspiration for researchers,
students, and system designers in computer vision as well as related
fields such as image processing, photogrammetry, medical image analysis,
and signal processing in general.